Mapping students' interest in a new domain: Connecting prior knowledge,interest, and self-efficacy with interesting tasks and a lasting desire to reengage

How students experience educational environments and the interconnections between their readiness, task experiences and their long-term desire to reengage with course content are critical questions for educators. Research postgraduate students (n = 310) at a research-intensive university in Hong Kong, engaging in a 24-h introductory teaching course, participated in this study. Learner readiness for the course was assessed as prior Domain interest, self-efficacy, and knowledge. Subsequently, students completed four formative assessments, reported their on-task interest in seven strategically chosen tasks and end-of-course Course and Domain interest. Longitudinal-SEM tested interconnections between readiness components, Task, Course and Domain interest. Initial self-efficacy beliefs for teaching predicted early Task interest, while Domain interest was a predictor of Task interest in explicitly practical task experiences. Strong interconnections between Task interest across the study were evident. Individual written and social discussion tasks presented strong contributions to future Course/Domain interest. Implications for theory and practice are discussed.     

“Was that interesting?” & “Does it matter?”: The implications of on-task learning experiences

Interest is a critical fuel for and outcome of learning. Building on and refocusing the Four-Phase Model of interest development, this study provides a window into the ecology of the learning experience and interest it generates. This research uses a novel mobile assessment platform to test learning experiences in three university courses (Organic chemistry, biochemistry, and introduction to physics for non-majors) and pilots a micro-analytic approach to capturing these experiences during lectures/tutorials. Students' interest in tasks, a single class, and the domain of study were collected with short surveys through an online mobile platform during class, immediately following task experiences. Latent variance-based modelling suggested strong forward connections between interest in most tasks. The connections between prior knowledge and interest with a future interest in course tasks varied strongly and were dependent on the nature of the tasks. The nuance of these connections and their implications for mobile assessment are discussed.